Parameter Estimation for Additive Hazard Model Recurrent Event Using Counting Process Approach
The Cox regression model is widely used for survival data analysis. The Cox model requires a proportional hazard. If the proportional hazard assumption is doubfult, then the additive hazard model can be used, where the covariates act in an additively to the baseline hazard function. If the obse...
| Main Authors: | , , |
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| Format: | Other |
| Language: | English |
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Mathematics and Statistics
2022
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/283977/1/116.Parameter-Estimation-for-Additive-Hazard-Model-Recurrent-Event-Using-Counting-Process-ApproachMathematics-and-Statistics.pdf |
| _version_ | 1826050723819814912 |
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| author | Wuryandari, Triastuti Gunardi, Gunardi Danardono, Danardono |
| author_facet | Wuryandari, Triastuti Gunardi, Gunardi Danardono, Danardono |
| author_sort | Wuryandari, Triastuti |
| collection | UGM |
| description | The Cox regression model is widely used for
survival data analysis. The Cox model requires a proportional
hazard. If the proportional hazard assumption is doubfult, then
the additive hazard model can be used, where the covariates
act in an additively to the baseline hazard function. If the
observed survival time is more than once for one individual
during the observation, it is called a recurrent event. The
additive hazard model measures risk difference to the effect
of a covariate in absolutely, while the proportional hazards
model measure hazard ratio in relatively. The risk coefficients
estimation in the additive hazard model mimics the multiplicative
hazard model, using partial likelihood methods. The
derivation of these estimators, outlined in the technical notes,
is based on the counting process approach. The counting
process approach was first developed by Aalen on 1975 which
combines elements of stochastic integration, martingale theory
and counting process theory. The method is applied to study
about the effect of supplementation on infant growth and
development. Based on the processing results, the factors that
affect the growth and development of the infant are gender,
treatment and mother’s education. |
| first_indexed | 2024-03-14T00:09:06Z |
| format | Other |
| id | oai:generic.eprints.org:283977 |
| institution | Universiti Gadjah Mada |
| language | English |
| last_indexed | 2024-03-14T00:09:06Z |
| publishDate | 2022 |
| publisher | Mathematics and Statistics |
| record_format | dspace |
| spelling | oai:generic.eprints.org:2839772023-11-27T02:43:17Z https://repository.ugm.ac.id/283977/ Parameter Estimation for Additive Hazard Model Recurrent Event Using Counting Process Approach Wuryandari, Triastuti Gunardi, Gunardi Danardono, Danardono Statistics The Cox regression model is widely used for survival data analysis. The Cox model requires a proportional hazard. If the proportional hazard assumption is doubfult, then the additive hazard model can be used, where the covariates act in an additively to the baseline hazard function. If the observed survival time is more than once for one individual during the observation, it is called a recurrent event. The additive hazard model measures risk difference to the effect of a covariate in absolutely, while the proportional hazards model measure hazard ratio in relatively. The risk coefficients estimation in the additive hazard model mimics the multiplicative hazard model, using partial likelihood methods. The derivation of these estimators, outlined in the technical notes, is based on the counting process approach. The counting process approach was first developed by Aalen on 1975 which combines elements of stochastic integration, martingale theory and counting process theory. The method is applied to study about the effect of supplementation on infant growth and development. Based on the processing results, the factors that affect the growth and development of the infant are gender, treatment and mother’s education. Mathematics and Statistics 2022 Other NonPeerReviewed application/pdf en https://repository.ugm.ac.id/283977/1/116.Parameter-Estimation-for-Additive-Hazard-Model-Recurrent-Event-Using-Counting-Process-ApproachMathematics-and-Statistics.pdf Wuryandari, Triastuti and Gunardi, Gunardi and Danardono, Danardono (2022) Parameter Estimation for Additive Hazard Model Recurrent Event Using Counting Process Approach. Mathematics and Statistics. https://efaidnbmnnnibpcajpcglclefindmkaj/https://www.hrpub.org/download/20220430/MS11-13426745.pdf DOI: 10.13189/ms.2022.100311 |
| spellingShingle | Statistics Wuryandari, Triastuti Gunardi, Gunardi Danardono, Danardono Parameter Estimation for Additive Hazard Model Recurrent Event Using Counting Process Approach |
| title | Parameter Estimation for Additive Hazard Model
Recurrent Event Using Counting Process Approach |
| title_full | Parameter Estimation for Additive Hazard Model
Recurrent Event Using Counting Process Approach |
| title_fullStr | Parameter Estimation for Additive Hazard Model
Recurrent Event Using Counting Process Approach |
| title_full_unstemmed | Parameter Estimation for Additive Hazard Model
Recurrent Event Using Counting Process Approach |
| title_short | Parameter Estimation for Additive Hazard Model
Recurrent Event Using Counting Process Approach |
| title_sort | parameter estimation for additive hazard model recurrent event using counting process approach |
| topic | Statistics |
| url | https://repository.ugm.ac.id/283977/1/116.Parameter-Estimation-for-Additive-Hazard-Model-Recurrent-Event-Using-Counting-Process-ApproachMathematics-and-Statistics.pdf |
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